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Learn fundamental concepts in data science through a recorded university lecture covering probability theory, random variables, and exploratory data analysis. Delve into essential topics including LaTeX usage, project requirements, grading policies, and academic integrity guidelines while exploring letter grid mapping techniques. Gain insights into course expectations, workload management, and available support resources through teaching assistants and TMS. Master practical skills for conducting data science projects and understand the importance of in-person class attendance for optimal learning outcomes in this comprehensive 75-minute session from the University of Utah's Data Science program.
Machine Learning Fundamentals - Probability and Random Variables - Lecture 3